Browsing by Author "Almeida, Pedro Gabriel De"
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- Data Collection Methodology to Assess Road Pavement Condition Using GNSS, Video Image and GISPublication . Santos, Bertha; Almeida, Pedro Gabriel De; Maganinho, Leonor Graciete de OliveiraTraffic loads, along with the environment, damage pavement over time. The degradation of pavement quality is reflected in the development of a diversity of pavement distresses, such as cracking, deformation or deterioration. These distresses may occur on the surface and/or in the pavement structure, having a determinant role in pavement’s quality. Aiming to increase the degree of reliability of the pavement distress data and reduce pavement observation time and visual inspection operations cost, this work presents the main steps proposed for a methodology to observe, record and evaluate flexible road pavement distresses to assess the quality of road pavements. This methodology is based on an in-vehicle inspection using GNSS and video image capture devices and in the use of Geographic Information System (GIS). Validation of the proposed methodology was made through a case study by comparing the results obtained on the in-vehicle inspection to those from a traditional visual inspection performed on foot. The similarity of results obtained by the two approaches allowed to conclude about the feasibility of the proposed methodology. Among the main advantages of the proposed methodology a highlight is on the possibility to identify, quantify and locate the most severe pavement distresses through the use of spatial tools available on GIS, producing information maps and reports that can be used in the decision-making process about road pavements rehabilitation and conservation.
- Validation of an indirect data collection method to assess airport pavement conditionPublication . Santos, Bertha; Almeida, Pedro Gabriel De; Feitosa, Ianca; Lima, DéboraIn this study the authors compare two methods for airport asphalt pavement distress data collection applied on the main runway of Amílcar Cabral international airport, located at Sal Island in Cape Verde. The two methods used for testing were traditional visual inspection (on-foot) and an indirect method using a vehicle equipped with image capture and recording, lasers and geolocation devices (in-vehicle inspection). The aim of this research is to contribute to the validation of the proposed low-cost in-vehicle pavement distress inspection system with semiautomatic data processing in order to be considered in the implementation of the pavement condition assessment component of airport pavement management systems (APMS). This is a particularly important component as from the collected distress data it is possible to assess the condition of the pavements and define intervention strategies. Validation of the indirect data collection method is evaluated by statistical comparison of the collected distress data and pavement condition index (PCI) obtained from both methods. Statistically non-significant differences between the result sets validate the proposed indirect method, however the analysis evidenced two aspects that need improvement in the proposed system, namely the quality of the captured images to identify distresses with lower severity level and inspector training for proper allocation of severity levels during image analysis. This results in significant advantages considering that the total amount of the runway pavement area is inspected. Inspection time is reduced and data collection cost can be reduced. Processing and results visualization on GIS environment allows revaluation of the dataset on the in-vehicle method. Data interpretation and measurements quality control becomes simpler and faster.